question:1

ANOVA Tests

a. Why are ANOVA tests so important?

b. What are the requirements for an ANOVA test?

c. What are the limitations of an ANOVA test?

d. When your date fails to meet the requirements for an ANOVA test, what do you do?

Question 2:

Two-Sample Tests for Proportions

What are the limitations of two-sample tests of proportions? Do these limitations present serious problems? Can the use of multiple confidence intervals for proportions overcome these limitations?

Question 3:

Statistical Power

What does the term statistical power mean? Why is statistical power so important? What is the problem with underpowered tests? Can a test be overpowered?

Question 4:

Type I and Type II Errors

What is the difference between Type I () and Type II () errors? How are Type I () and Type II () errors related? What affects the probability of Type I () and Type II () errors? Which type of error is considered more serious?

Question 5:

What is Effect Size? Why is it a critically important concept?

Broadly speaking Effect Size or ES are measures that are used to determine whether the significance. It may be worthwhile to redo such tests with a larger sample.

Question 6:

What are p-values? Why are they important? What does a p-value tell us? Why are p-values often misunderstood and misused? When do we reject or fail to reject the Null Hypothesis based on p-values?

Question 7:

What is the difference between a significance level and a confidence level?

How does this difference highlight the difference between Null Hypothesis Significance Tests and Confidence Intervals?

Question 8:

What is a Null Hypothesis? What does the word "null" mean? How does the NullHypothesis differ from the Alternate Hypothesis? Can we have a third hypothesis?